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Genome-scale reconstruction and in silico analysis of the Clostridium acetobutylicum ATCC 824 metabolic network

  • Genomics and Proteomics
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Abstract

To understand the metabolic characteristics of Clostridium acetobutylicum and to examine the potential for enhanced butanol production, we reconstructed the genome-scale metabolic network from its annotated genomic sequence and analyzed strategies to improve its butanol production. The generated reconstructed network consists of 502 reactions and 479 metabolites and was used as the basis for an in silico model that could compute metabolic and growth performance for comparison with fermentation data. The in silico model successfully predicted metabolic fluxes during the acidogenic phase using classical flux balance analysis. Nonlinear programming was used to predict metabolic fluxes during the solventogenic phase. In addition, essential genes were predicted via single gene deletion studies. This genome-scale in silico metabolic model of C. acetobutylicum should be useful for genome-wide metabolic analysis as well as strain development for improving production of biochemicals, including butanol.

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Acknowledgments

We wish to express thanks to Peter Schumann and Jong-Soon Choi for the determination of cell wall and amino acid composition, respectively. Also, we are grateful to Jin Young Lee and Yu Sin Jang for discussion on cell cultivation and analytical procedure. Finally, we thank Tae Yong Kim and Hyun Uk Kim for discussion on flux balance analysis. This work was supported by the Korea–Australia Collaborative Research Project on the Development of Sucrose-Based Bioprocess Platform (N02071165) from the Korean Ministry of Knowledge Economy. Further support by LG Chem Chair Professorship and Microsoft are appreciated.

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Authors and Affiliations

  1. Metabolic and Biomolecular Engineering National Research Laboratory, Department of Chemical & Biomolecular Engineering (BK21 Program), BioProcess Engineering Research Center, Center for Systems and Synthetic Biotechnology and Institute for the BioCentury, KAIST, Daejeon, 305-701, Republic of Korea

    Joungmin Lee, Hongseok Yun & Sang Yup Lee

  2. Department of Bioengineering, University of California, San Diego, La Jolla, CA, 92093-0412, USA

    Adam M. Feist & Bernhard Ø. Palsson

  3. Department of Bio and Brain Engineering, Department of Biological Sciences and Bioinformatics Research Center, KAIST, Daejeon, 305-701, Republic of Korea

    Sang Yup Lee

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  1. Joungmin Lee
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  2. Hongseok Yun
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  3. Adam M. Feist
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  4. Bernhard Ø. Palsson
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  5. Sang Yup Lee
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Correspondence to Sang Yup Lee.

Additional information

J. L. and H. Y. equally contributed to this work.

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Supplementary Data 1

Gene–protein–reaction relationship, metabolite abbreviation, and whole reaction set used in the model. (PDF 548 KB)

Supplementary Data 2

Biomass composition of C. acetobutylicum, ATCC 824 used in the model. (PDF 79.6 KB)

Supplementary Data 3

The list of essential and partially essential genes in synthetic medium from in silico gene deletion analysis. (PDF 60.8 KB)

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Lee, J., Yun, H., Feist, A.M. et al. Genome-scale reconstruction and in silico analysis of the Clostridium acetobutylicum ATCC 824 metabolic network. Appl Microbiol Biotechnol 80, 849–862 (2008). https://doi.org/10.1007/s00253-008-1654-4

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